ML Systems Debugger & Prompt Engineer (Remote)

DataAnnotation; Fairbanks (AK); Remote; USD 83,000 - 207,000; Full time

Job summary

DataAnnotation is at the forefront of scalable AI contribution, enabling 1M+ experts to train the world’s leading models. We seek a Machine Learning Engineer to stress-test model reasoning, design evaluation prompts, and craft robust solutions grounded in real practitioner experience.

You’ll write prompts, review outputs for subtle errors, and produce correct solutions, all while leveraging Python and modern ML stacks in a flexible, remote setting.

Qualifications

• Hands-on experience training, evaluating, or deploying models professionally or in serious personal work.
• Comfort with the modern ML stack; most tasks assume Python and PyTorch or JAX.
• Clear written English: your explanations are the training signal.
• No degree required. We care about what you can do, not where you learned it.

Responsibilities

• Write prompts that probe how models reason about training, evaluation, debugging, and productionizing ML systems.
• Review AI output for subtle errors: leaky evaluations, wrong loss formulations, and misdiagnosed training failures.
• Write the correct solution when the model falls short, grounded in real practitioner experience.

Skills

Model training

Model evaluation

Model deployment

PyTorch/JAX

Tools

PyTorch

JAX

Job description

DataAnnotation is at the forefront of scalable AI contribution, enabling 1M+ experts to train the world’s leading models. We seek a Machine Learning Engineer to stress-test model reasoning, design evaluation prompts, and craft robust solutions grounded in real practitioner experience.

You’ll write prompts, review outputs for subtle errors, and produce correct solutions, all while leveraging Python and modern ML stacks in a flexible, remote setting.